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Article Type:
Research Article

Retrieval of Model Initial Fields from Single-Doppler Observations of a Supercell Thunderstorm. Part I: Single-Doppler Velocity Retrieval

Stephen S. Weygandt Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Alan Shapiro Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Kelvin K. Droegemeier Center for Analysis and Prediction of Storms, and School of Meteorology, University of Oklahoma, Norman, Oklahoma

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Print Publication:
01 Mar 2002
DOI:
https://doi.org/10.1175/1520-0493(2002)130<0433:ROMIFF>2.0.CO;2
Page(s):
433–453
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Abstract

In this two-part study, a single-Doppler parameter retrieval technique is developed and applied to a real-data case to provide initial conditions for a short-range prediction of a supercell thunderstorm. The technique consists of the sequential application of a single-Doppler velocity retrieval (SDVR), followed by a variational velocity adjustment, a thermodynamic retrieval, and a moisture specification step. By utilizing a sequence of retrievals in this manner, some of the difficulties associated with full-model adjoints (possible solution nonuniqueness and large computational expense) can be circumvented. In Part I, the SDVR procedure and present results from its application to a deep-convective storm are discussed. Part II focuses on the thermodynamic retrieval and subsequent numerical prediction.

For the SDVR, Shapiro's reflectivity conservation-based method is adapted by applying it in a moving reference frame. Verification of the retrieved wind fields against corresponding dual-Doppler analyses indicates that the best skill scores are obtained for a reference frame moving with the mean wind, which effectively reduces the problem to a perturbation retrieval. A decomposition of the retrieved wind field into mean and perturbation components shows that the mean wind accounts for a substantial portion of the total retrieved azimuthal velocity. At low levels, where the retrieval skill scores are especially good, the retrieved perturbation azimuthal velocity is mostly associated with the polar component of vorticity. Missing from the retrieved fields (compared to the dual-Doppler analysis) is most of the low-level azimuthal convergence. Consistent with this result, most of the retrieved updraft is associated with convergence of the perturbation radial velocity, which is calculated from the observed radial velocity and directly used in the wind retrieval.

* Current affiliation: NOAA Office of Atmospheric Research, Forecast Systems Laboratory, Boulder, Colorado.

Corresponding author address: Stephen S. Weygandt, NOAA Forecast Systems Laboratory, 325 Broadway, R/FS1, Boulder, CO 80305-3328. Email: weygandt@fsl.noaa.gov

Abstract

In this two-part study, a single-Doppler parameter retrieval technique is developed and applied to a real-data case to provide initial conditions for a short-range prediction of a supercell thunderstorm. The technique consists of the sequential application of a single-Doppler velocity retrieval (SDVR), followed by a variational velocity adjustment, a thermodynamic retrieval, and a moisture specification step. By utilizing a sequence of retrievals in this manner, some of the difficulties associated with full-model adjoints (possible solution nonuniqueness and large computational expense) can be circumvented. In Part I, the SDVR procedure and present results from its application to a deep-convective storm are discussed. Part II focuses on the thermodynamic retrieval and subsequent numerical prediction.

For the SDVR, Shapiro's reflectivity conservation-based method is adapted by applying it in a moving reference frame. Verification of the retrieved wind fields against corresponding dual-Doppler analyses indicates that the best skill scores are obtained for a reference frame moving with the mean wind, which effectively reduces the problem to a perturbation retrieval. A decomposition of the retrieved wind field into mean and perturbation components shows that the mean wind accounts for a substantial portion of the total retrieved azimuthal velocity. At low levels, where the retrieval skill scores are especially good, the retrieved perturbation azimuthal velocity is mostly associated with the polar component of vorticity. Missing from the retrieved fields (compared to the dual-Doppler analysis) is most of the low-level azimuthal convergence. Consistent with this result, most of the retrieved updraft is associated with convergence of the perturbation radial velocity, which is calculated from the observed radial velocity and directly used in the wind retrieval.

* Current affiliation: NOAA Office of Atmospheric Research, Forecast Systems Laboratory, Boulder, Colorado.

Corresponding author address: Stephen S. Weygandt, NOAA Forecast Systems Laboratory, 325 Broadway, R/FS1, Boulder, CO 80305-3328. Email: weygandt@fsl.noaa.gov

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  • Brewster, K. A., 1984: Kinetic energy evolution in a developing severe thunderstorm. M.S. thesis, School of Meteorology, University of Oklahoma, Norman, OK, 171 pp.

    • Search Google Scholar
    • Export Citation

  • Burgess, D. W., and L. R. Lemon, 1990: Severe thunderstorm detection by radar. Radar in Meteorology, D. Atlas, Ed., Amer. Meteor. Soc., 619–647.

    • Search Google Scholar
    • Export Citation

  • Burgess, D. W., and M. A. Magsig, 1998: Recent observations of tornado development at near range to WSR-88D radars. Preprints, 19th Conf. on Severe Local Storms, Minneapolis, MN, Amer. Meteor. Soc., 756–759.

    • Search Google Scholar
    • Export Citation

  • Cressman, G., 1959: An operational objective analysis system. Mon. Wea. Rev, 87 , 367–374.

  • Crook, A., 1994: Numerical experiments initialized with radar-derived winds. Part I: Simulated data experiments. Mon. Wea. Rev, 122 , 1189–1203.

    • Search Google Scholar
    • Export Citation

  • Crook, A., and J. D. Tuttle, 1994: Numerical experiments initialized with radar-derived winds. Part II: Forecasts of three gust front cases. Mon. Wea. Rev, 122 , 1204–1217.

    • Search Google Scholar
    • Export Citation

  • Dowell, D. C., and H. B. Bluestein, 1997: The Arcadia, Oklahoma, storm of 17 May 1981: Analysis of a supercell during tornadogenesis. Mon. Wea. Rev, 125 , 2562–2582.

    • Search Google Scholar
    • Export Citation

  • Droegemeier, K. K., 1990: Toward a science of storm-scale prediction. Preprints, 16th Conf. on Severe Local Storms, Kananaskis Park, Alberta, Canada, Amer. Meteor. Soc., 256–262.

    • Search Google Scholar
    • Export Citation

  • Droegemeier, K. K., 1997: Numerical prediction of thunderstorms: Challenges, potential benefits and results from real-time operational tests. WMO Bull, 46 (4,) 1–13.

    • Search Google Scholar
    • Export Citation

  • Funk, T. W., V. L. DeWald, and Y. J. Lin, 1998: A detailed WSR-88D Doppler radar evaluation of a damaging bow-echo event on 14 May 1995 over north-central Kentucky. Preprints, 19th Conf. on Severe Local Storms, Minneapolis, MN, Amer. Meteor. Soc., 436–439.

    • Search Google Scholar
    • Export Citation

  • Gal-Chen, T., 1978: A method for initializing the anelastic equations: Implications for matching models with observations. Mon. Wea. Rev, 106 , 587–606.

    • Search Google Scholar
    • Export Citation

  • Gal-Chen, T., 1982: Errors in fixed and moving frame of references: Applications for conventional and Doppler radar analysis. J. Atmos. Sci, 39 , 2279–2300.

    • Search Google Scholar
    • Export Citation

  • Gao, J., M. Xue, A. Shapiro, Q. Xu, and K. K. Droegemeier, 2001: Three-dimensional simple adjoint velocity retrievals from single-Doppler radar. J. Atmos. Oceanic Technol, 18 , 26–38.

    • Search Google Scholar
    • Export Citation

  • Glass, F. H., and M. F. Britt, 2000: Close range WSR-88D observations of several tornadic storms. Preprints, 20th Conf. on Severe Local Storms, Orlando, FL, Amer. Meteor. Soc., 190–193.

    • Search Google Scholar
    • Export Citation

  • Hane, C. E., and B. C. Scott, 1978: Temperature and pressure perturbations within convective clouds derived from detailed air motion information: Preliminary testing. Mon. Wea. Rev, 106 , 654–661.

    • Search Google Scholar
    • Export Citation

  • Hauser, D., and P. Amayenc, 1986: Retrieval of cloud water and water vapor contents from Doppler radar data in a tropical squall line. J. Atmos. Sci, 43 , 823–838.

    • Search Google Scholar
    • Export Citation

  • Hermes, L. G., A. Witt, S. D. Smith, D. Klingle-Wilson, D. Morris, G. J. Stumpf, and M. D. Eilts, 1993: The gust-front detection and wind-shift detection algorithms for the terminal Doppler weather radar system. J. Atmos. Oceanic Technol, 10 , 693–709.

    • Search Google Scholar
    • Export Citation

  • Klazura, G. E., and D. A. Imy, 1993: A description of the initial set of analysis products available from the NEXRAD WSR-88D system. Bull. Amer. Meteor. Soc, 74 , 1293–1311.

    • Search Google Scholar
    • Export Citation

  • Laroche, S., and I. Zawadzki, 1994: A variational analysis method for the retrieval of three-dimensional wind field from single-Doppler radar data. J. Atmos. Sci, 51 , 2664–2682.

    • Search Google Scholar
    • Export Citation

  • Laroche, S., and I. Zawadzki, 1995: Retrievals of horizontal winds from single-Doppler clear-air data by methods of cross-correlation and variational analysis. J. Atmos. Oceanic Technol, 12 , 721–738.

    • Search Google Scholar
    • Export Citation

  • Lazarus, S. M., 1996: The assimilation and prediction of a Florida multicell storm using single-Doppler data. Ph.D. dissertation, University of Oklahoma, 340 pp.

    • Search Google Scholar
    • Export Citation

  • Lazarus, S. M., A. Shapiro, and K. Droegemeier, 2001: Application of the Zhang–Gal-Chen single-Doppler velocity retrieval to a deep-convective storm. J. Atmos. Sci, 58 , 998–1016.

    • Search Google Scholar
    • Export Citation

  • LeDimet, F. X., and O. Talagrand, 1986: Variational algorithms for analysis and assimilation of meteorological observations: Theoretical aspects. Tellus, 38A , 97–110.

    • Search Google Scholar
    • Export Citation

  • Lemon, L. R., and D. W. Burgess, 1980: Magnitude and implications of high speed outflow at severe storm summits. Preprints, 19th Conf. on Radar Meteorology, Miami, FL, Amer. Meteor. Soc., 364–368.

    • Search Google Scholar
    • Export Citation

  • Lewis, J., and J. Derber, 1985: The use of adjoint equations to solve a variational problem with advective constraints. Tellus, 37A , 309–322.

    • Search Google Scholar
    • Export Citation

  • Lilly, D. K., 1990: Numerical prediction of thunderstorms—Has its time come? Quart. J. Roy. Meteor. Soc, 116 , 779–798.

  • Lin, Y., P. S. Ray, and K. W. Johnson, 1993: Initialization of a modeled convective storm using Doppler radar–derived fields. Mon. Wea. Rev, 121 , 2757–2775.

    • Search Google Scholar
    • Export Citation

  • Navon, I. M., X. L. Zou, J. Derber, and J. Sela, 1992: Variational data assimilation with an adiabatic version of the NMC spectral model. Mon. Wea. Rev, 120 , 1433–1446.

    • Search Google Scholar
    • Export Citation

  • O'Brien, J. J., 1970: Alternative solutions to the classical vertical velocity problem. J. Appl. Meteor, 9 , 197–203.

  • Qiu, C. J., and Q. Xu., 1992: A simple adjoint method of wind analysis for single-Doppler data. J. Atmos. Oceanic Technol, 9 , 588–598.

    • Search Google Scholar
    • Export Citation

  • Ray, P. S., B. C. Johnson, K. W. Johnson, J. S. Bradberry, J. J. Stephens, K. K. Wagner, R. B. Wilhelmson, and J. B. Klemp, 1981: The morphology of several tornadic storms on 20 May 1977. J. Atmos. Sci, 38 , 1643–1663.

    • Search Google Scholar
    • Export Citation

  • Rhinehart, R. E., 1979: Internal storm motions from single non-Doppler weather radar. NCAR Tech. Note NCAR/TN-146+STR, 262 pp.

  • Roberts, R. D., and J. W. Wilson, 1989: A proposed microburst nowcasting procedure using single-Doppler radar. J. Appl. Meteor, 28 , 285–303.

    • Search Google Scholar
    • Export Citation

  • Roux, F., 1985: Retrieval of thermodynamic fields from multiple Doppler radar data using the equations of motion and thermodynamic equation. Mon. Wea. Rev, 113 , 2142–2157.

    • Search Google Scholar
    • Export Citation

  • Rutledge, S. A., and P. V. Hobbs, 1983: The mesoscale and microscale structure and organization of clouds and precipitation in a mid-latitude cyclone. VIII: A model for the “seeder-feeder” process in warm-frontal rainbands. J. Atmos. Sci, 40 , 1185–1206.

    • Search Google Scholar
    • Export Citation

  • Rutledge, S. A., and P. V. Hobbs, 1984: The mesoscale and microscale structure and organization of clouds and precipitation in a mid-latitude cyclone. XII: A diagnostic modeling study of precipitation development in narrow cold-frontal rainbands. J. Atmos. Sci, 41 , 2949–2972.

    • Search Google Scholar
    • Export Citation

  • Shapiro, A., and S. Lazarus, 1993: A modified dynamic recovery technique for cloud-scale numerical models. Preprints, 17th Conf. on Severe Local Storms, St. Louis, MO, Amer. Meteor. Soc., 455–459.

    • Search Google Scholar
    • Export Citation

  • Shapiro, A., S. Ellis, and J. Shaw, 1995a: Single-Doppler velocity retrievals with Phoenix II data: Clear air and microburst wind retrievals in the planetary boundary layer. J. Atmos. Sci, 52 , 1265–1287.

    • Search Google Scholar
    • Export Citation

  • Shapiro, A., and and Coauthors, 1995b: Highlights from a single-Doppler velocity retrieval intercomparison project. Preprints, Sixth Conf. on Aviation Weather Systems, Dallas, TX, Amer. Meteor. Soc., 541–546.

    • Search Google Scholar
    • Export Citation

  • Smythe, G. R., and D. S. Zrnic, 1983: Correlation analysis of Doppler radar data and retrieval of the horizontal wind. J. Climate Appl. Meteor, 22 , 297–311.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and A. Crook, 1994: Wind and thermodynamic retrieval from single-Doppler measurements of a gust front observed during Phoenix II. Mon. Wea. Rev, 122 , 1075–1091.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and A. Crook, 1996: Comparison of thermodynamic retrieval by the adjoint method with the traditional retrieval method. Mon. Wea. Rev, 124 , 308–324.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and A. Crook, 1997: Dynamic and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part I: Model development and simulated data experiments. J. Atmos. Sci, 54 , 1642–1661.

    • Search Google Scholar
    • Export Citation

  • Sun, J., and A. Crook, 1998: Dynamic and microphysical retrieval from Doppler radar observations using a cloud model and its adjoint. Part II: Retrieval experiments of an observed Florida convective storm. J. Atmos. Sci, 55 , 835–852.

    • Search Google Scholar
    • Export Citation

  • Sun, J., D. W. Flicker, and D. K. Lilly, 1991: Recovery of three-dimensional wind and temperature fields from simulated single-Doppler radar data. J. Atmos. Sci, 48 , 876–890.

    • Search Google Scholar
    • Export Citation

  • Talagrand, O., and P. Courtier, 1987: Variational assimilation of meteorological observations with the adjoint vorticity equations. Part I: Theory. Quart. J. Roy. Meteor. Soc, 113 , 1311–1328.

    • Search Google Scholar
    • Export Citation

  • Taylor, G. I., 1938: The spectrum of turbulence. Proc. Roy. Soc. London, A164 , 476–490.

  • Thepaut, J., D. Vasiljevic, and P. Coutier, 1993: Variational assimilation of conventional meteorological observations with a multilevel primitive equation model. Quart. J. Roy. Meteor. Soc, 119 , 153–186.

    • Search Google Scholar
    • Export Citation

  • Trapp, R. J., and C. A. Doswell, 2000: Radar data objective analysis. J. Atmos. Oceanic Technol, 17 , 105–120.

  • Tuttle, J. D., and G. B. Foote, 1990: Determination of the boundary layer airflow from a single Doppler radar. J. Atmos. Oceanic Technol, 7 , 218–232.

    • Search Google Scholar
    • Export Citation

  • Uyeda, H., and D. S. Zrnic, 1986: Automatic detection of gust fronts. J. Atmos. Oceanic Technol, 3 , 36–50.

  • Verlinde, J., and W. R. Cotton, 1990: A critical look at microphysical retrieval algorithms. Preprints, Conf. on Cloud Physics, San Francisco, CA, Amer. Meteor. Soc., 453–457.

    • Search Google Scholar
    • Export Citation

  • Verlinde, J., and W. R. Cotton, 1993: Fitting microphysical observations of non-steady convective clouds to a numerical model: An application of the adjoint technique of data assimilation to a kinematic model. Mon. Wea. Rev, 121 , 2776–2793.

    • Search Google Scholar
    • Export Citation

  • Weygandt, S. S., A. Shapiro, and K. K. Droegemeier, 2002: Retrieval of model initial fields from single-Doppler observations of a supercell thunderstorm. Part II: Thermodynamic Retrieval and numerical prediction. Mon. Wea. Rev, 130 , 454–476.

    • Search Google Scholar
    • Export Citation

  • Wilson, J. W., R. D. Roberts, C. Kessinger, and J. McCarthy, 1984: Microburst wind structure and evaluation of Doppler radar for airport wind shear detection. J. Appl. Meteor, 23 , 898–915.

    • Search Google Scholar
    • Export Citation

  • Wilson, J. W., N. A. Crook, C. K. Mueller, J. Sun, and M. Dixon, 1998: Nowcasting thunderstorms: A status report. Bull. Amer. Meteor. Soc, 79 , 2079–2099.

    • Search Google Scholar
    • Export Citation

  • Witt, A., and S. P. Nelson, 1984: The relationship between upper-level divergent outflow magnitude as measured by Doppler radar and hailstorm intensity. Preprints, 22nd Conf. on Radar Meteorology, Zurich, Switzerland, Amer. Meteor. Soc., 108–111.

    • Search Google Scholar
    • Export Citation

  • Xu, Q., 1996: Generalized adjoint for physical processes with parameterized discontinuities. Part I: Basic issues and heuristic examples. J. Atmos. Sci, 53 , 1123–1142.

    • Search Google Scholar
    • Export Citation

  • Xu, Q., C. J. Qiu, and J. X. Yu, 1994a: Adjoint method retrievals of low-altitude wind fields from single-Doppler reflectivity measured during Phoenix-II. J. Atmos. Oceanic Technol, 11 , 275–288.

    • Search Google Scholar
    • Export Citation

  • Xu, Q., C. J. Qiu, and J. X. Yu, 1994b: Adjoint method retrievals of low-altitude wind fields from single-Doppler wind data. J. Atmos. Oceanic Technol, 11 , 579–585.

    • Search Google Scholar
    • Export Citation

  • Xu, Q., C. J. Qiu, H. D. Gu, and J. X. Yu, 1995: Simple adjoint retrievals of microburst winds from single-Doppler data. Mon. Wea. Rev, 123 , 1822–1833.

    • Search Google Scholar
    • Export Citation

  • Xu, Q., H. D. Gu, and S. Yang, 2001: Simple adjoint method for three-dimensional wind retrievals from single-Doppler data. Quart. J. Roy. Meteor. Soc, 127 , 1053–1067.

    • Search Google Scholar
    • Export Citation

  • Xue, M., K. K. Droegemeier, and V. Wong, 2000: The Advanced Regional Prediction System (ARPS)—A multiscale nonhydrostatic atmospheric simulation and prediction tool. Part I: Model dynamics and verification. Meteor. Atmos. Phys, 75 , 161–193.

    • Search Google Scholar
    • Export Citation

  • Xue, M., and and Coauthors, 2001: The Advanced Regional Prediction System (ARPS)—A multiscale nonhydrostatic atmospheric simulation and prediction tool. Part II: Model physics and applications. Meteor. Atmos. Phys, 75 , 161–193.

    • Search Google Scholar
    • Export Citation

  • Xue, M., A. Shapiro, and K. Brewster, and and Coauthors, 1995: ARPS User's Guide, Version 4.0. Center for Analysis and Prediction of Storms, 380 pp.

    • Search Google Scholar
    • Export Citation

  • Zhang, J., and T. Gal-Chen, 1996: Single-Doppler wind retrieval in the moving frame of reference. J. Atmos. Sci, 53 , 2609–2623.

  • Ziegler, C. L., 1985: Retrieval of thermal and microphysical variables in observed convective storms. Part I: Model development and preliminary testing. J. Atmos. Sci, 42 , 1487–1509.

    • Search Google Scholar
    • Export Citation

  • Ziegler, C. L., 1988: Retrieval of thermal and microphysical variables in observed convective storms. Part II: Sensitivity of cloud processes to variation of the microphysical parameterization. J. Atmos. Sci, 45 , 1072–1090.

    • Search Google Scholar
    • Export Citation

  • Zou, X. L., I. M. Navon, and J. Sela, 1993: Variational data assimilation with threshold processes using the NMC multilevel primitive-equation model. Tellus, 45A , 370–387.

    • Search Google Scholar
    • Export Citation

  • Zupanski, M., 1993: Regional four-dimensional variational data assimilation in a quasi-operational forecasting environment. Mon. Wea. Rev, 121 , 2396–2408.

    • Search Google Scholar
    • Export Citation
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